How did you catch the customer analytics bug?

JK: I always preferred statistics to finance in undergrad, so I had the bug back then. After I graduated, I took the finance path but realized it wasn’t what I wanted to do day-to-day. My goal was to get back into statistics, so I applied for Wharton MBA since Wharton is known for being a quant-heavy program.

How did you focus your MBA work to achieve your career goals?

JK: By the time I started the MBA program, I had five years of business experience and four years of business undergrad, so I wasn’t looking for more core business courses. In addition to taking more quantitative courses, I decided I also wanted to learn R. So I tracked down Ph.D. students who were willing to teach me. There are so many great resources at Wharton and UPenn that students can take advantage of—you just need to seek them out.

What classes were the most important to the work you do today?

JK: Hands down, the best courses I took were Peter Fader’s Applied Probability Models in Marketing [MKTG 476/776] and the Experiments for Business Decision Making class [MKTG 309/809].

Where do you see current opportunities in customer analytics?

JK: Right now, the team I work with includes software engineers and business analysts. As we evolve, there’s a need for someone with both technical and quantitative skills to bridge the gap between both roles and still be able to understand customer behavior.

What advice would you offer to Wharton students?

JK: Customer analytics offers infinite opportunities and entry points—there’s no single, linear way to enter the field. Take advantage of the resources you have at Wharton. Take it upon yourself to be proactive, to learn what you’re interested in, and be focused about going after it.